2243 Fractal dimension and lacunarity as predictive radiomic features for relapse in pulmonary nodules

Abstract

Radiomic features such as fractal dimension and lacunarity have shown promising results in tumor analysis, characterizing the structural complexity and internal heterogeneity of pulmonary nodules in CT images. However, select those providing relevant information without redundancy of the large number of available radiomic variables is necessary. This preliminary study investigates the predictive potential of fractal-dimension and lacunarity for early relapse in patients with pulmonary nodules treated with SBRT.